List of Tables 6.1 Standard RC components used on the FLASH car. . . . . . . . . . . . . . . 53 6.2 Sensors used on the FLASH car. . . . . . . . . . . . . . . . . . . . . . . . . . 55 6.3 Technical information for the PIC microcontroller. . . . . . . . . . . . . . . . 56 6.4 Technical information for the C31 DSP. . . . . . . . . . . . . . . . . . . . . . 60 6.5 Technical information for the DSP Starter Kit. . . . . . . . . . . . . . . . . . 61 6.6 Format for the PIC control word . . . . . . . . . . . . . . . . . . . . . . . . 67 6.7 Technical information for the infrared sensors. . . . . . . . . . . . . . . . . . 68 6.8 Technical information for the Hall effect sensors. . . . . . . . . . . . . . . . . 69 6.9 Technical information for the digital camera. . . . . . . . . . . . . . . . . . . 71 6.10 Technical information for the ultrasound sensor. . . . . . . . . . . . . . . . . 72 xi Chapter 1 Introduction The automation of the driving task has been the subject of much research recently. Auto- mobile manufacturers have developed and are continuing to develop systems for cars that alleviate the driver’s need to monitor and control all aspects of the vehicle. Such systems include antilock braking systems, traction control, cruise control and others in development that will surely alleviate the driving burden in years to come. 1.1 Motvation Why automate the driving task? One of the major reasons is safety. In 2000, there were approximately 6,394,000 police reported motor vehicle traffic crashes, resulting in 3,189,000 people being injured and 41,821 lives lost [1]. Accidents on our roadways not only cause injuries and fatalities, but they also have a huge economic impact [2]. Many accidents are caused by human error and eliminating this error will reduce the number of injuries and fatalities on our roadways. Human driving error may be caused by a number of factors including fatigue and distraction. During long drives on the highway, the driver must constantly monitor the road conditions and react to them over an extended period of time. Such constant attentiveness is tiring and the resulting fatigue may reduce the driver’s reaction time. Additionally, the driver may be distracted from the task of driving by conversations with other passengers, tuning the radio, using a cell phone, etc. Such distractions may also lead to accidents. According to [3], driver distraction was a factor in 11% of fatal crashes and 25-30% of injury and property- damage-only crashes in 1999. Viewed from another perspective however, a car capable of driving itself can allow the occupants to perfom non-driving tasks safely while traveling to their destination. Another reason to automate cars is to alleviate congestion on the highways. A method called 1 Patricia Mellodge Chapter 1. Introduction 2 ”platooning” would allow cars to drive at highway speed while only a few feet apart. Since the electronics on the car can respond faster than a human, cars would be able to drive much closer together. This would allow much more efficient use of the existing highways in a safe manner. 1.2 Autonomous Vehicles The inventions of the integrated circuit (IC) and later, the microcomputer, were major factors in the development of electronic control in automobiles. The importance of the microcomputer cannot be overemphasized as it is the ”brain” that controls many systems in today’s cars. For example, in a cruise control system, the driver sets the desired speed and enables the system by pushing a button. A micro computer then monitors the actual speed of the vehicle using data from velocity sensors. The actual speed is compared to the desired speed and the controller adjusts the throttle as necessary. See [4] for a complete overview of electronic control systems used in cars today. The U.S. government has also played a role in encouraging the technological advancement of automobiles and development of intelligent transportation systems (ITS). In the early 1990s, the Center for Transportation Research (now known as the Virginia Tech Transportation In- stitute (VTTI)) received funding to build the Smart Road, a 6 mile highway connecting Blacksburg, VA to Interstate 81. The road was built to be ”intelligent”, with sensors em- bedded to alert a traveling vehicle to road conditions. Advanced automotive technologies such as lane detection, obstacle detection, adaptive cruise control, collision avoidance, and lateral control were intended to be developed using the Smart Road as a testing ground [5]. A completely autonomous vehicle is one in which a computer performs all the tasks that the human driver normally would. Ultimately, this would mean getting in a car, entering the destination into a computer, and enabling the system. From there, the car would take over and drive to the destination with no human input. The car would b e able to sense its environment and make steering and speed changes as necessary. This scenario would require all of the automotive technologies mentioned above: lane detec- tion to aid in passing slower vehicles or exiting a highway; obstacle detection to locate other cars, pedestrians, animals, etc.; adaptive cruise control to maintain a safe speed; collision avoidance to avoid hitting obstacles in the roadway; and lateral control to maintain the car’s position on the roadway. In addition, sensors would be needed to alert the car to road or weather conditions to ensure safe traveling speeds. For example, the car would need to slow down in snowy or icy conditions. We perform many tasks while driving without even thinking about it. Completely automat- ing the car is a challenging task and is a long way off. However, advances have been made in the individual systems. Cruise control is common in cars today. Adaptive cruise control, in which the car slows if it detects a slower moving vehicle in front of it, is starting to be- Patricia Mellodge Chapter 1. Introduction 3 Figure 1.1: Block diagram of the lateral controller. come available on higher-end models. In addition, some cars come equiped with sensors to determine if an obstacle is near and sounds an audible warning to the driver when it is too close. The focus of this work is lateral control. With this type of vehicle control, the driver would be able to remove his hands from the steering wheel and let the car steer itself. Here, the idea is that the car has some desired path to follow. Sensors on the car must be able to detect the location of the desired path. The error between the desired path and the car is calculated and the microcomputer acting as the controller determines how to turn the steering wheels to follow the correct path. Fig. 1.1 shows the feedback control system for lateral control. The lateral controller’s purp ose is to follow the desired path. It does not determine what the desired path is. A higher level planner is responsible for that task. This planner may take into account data from other sensors so as to avoid collisions or arrive at its ultimate destination. The lateral controller does not know or need to know such high level information. It only needs to know the car’s location with respect to the desired path. 1.3 Previous Research 1.3.1 Modeling Designing a lateral controller requires a model of the vehicle’s behavior. There have been two approaches to this modeling: dynamic and kinematic. Dynamic modeling takes into account such factors as the vehicle’s weight, center of gravity, cornering stiffness, wheel slippage, and others. The resulting equations, as used in [6], are very complex and difficult to work with. In addition, it may be difficult to measure Patricia Mellodge Chapter 1. Introduction 4 parameters such as cornering stiffness. However, they give a highly accurate portrayal of the vehicle’s behavior and the controllers designed with them are robust to those dynamics. A simpler approach to modeling (and the one used here) is to ignore the dynamics of the system and only use its kinematics. The effects of weight, inertia, etc. are ignored and the model is derived using only the nonholonomic contraints of the system as in [7]. The advantage of this model is that it is much simpler than the dynamic one. However, it is a much less accurate depiction of the actual system as a result. Details of this model are given in Chapter 3. 1.3.2 Controllers There has been much research in the area of control theory and many modern controllers have been developed as a result. The most widely used controller is still the PID (proportional, integral, derivative) controller because of it simplicity and ease of implementation. However, with the increasing power of computers and microprocessors, more robust and more powerful controllers are able to be implemented in many systems. Among the classes of controllers that have been implemented are: fuzzy controllers, neural networks, and adaptive controllers. In addition, specific controllers are developed for indi- vidual applications. In this work, an input scaling controller is implemented and is described in Chapter 3. 1.3.3 Sensors The controller must know where the path is located with respect to the vehicle. This location information is provided by sensors on the vehicle. Various sensors are available to perform this task and their accuracy and ease of implementation vary. Also, certain types of sensors require changes to the roads themselves while others can be used on existing roads. Cameras Much research has been devoted to the use of cameras in autonomous vehicles. The camera is used to take images of the roadway in front of the vehicle. Image processing is then performed to extract information from the image about the car’s location on the road. This type of sensing is most like that used by human drivers. The camera sees ahead and the controller can make steering adjustments based on how the road is curving up ahead. Patricia Mellodge Chapter 1. Introduction 5 Infrared Sensors Infrared sensors have been used to detect white lines on dark pavement. Infrared light is emitted from LEDs under the car. The light is reflected by the white line and absorbed by the dark pavement. Sensors detect the light that is reflected back and so the location of the white line is known. This method assumes that the car is to follow the white line. Magnetic Sensors Magnetic sensors work by detecting the presence of a magnetic field. Sensors under the car detect magnets embedded in the roadway. This method is very similar to the use of infrared sensors but requires major changes to the infrastructure since most roads do not have magnets embedded in them. Radar The use of radar follows the same principle as infrared technology except a different kind of energy is used. An RF signal is emitted towards the road and it may be redirected back by a reflector stripe. Thus position information is provided to the controller. Each of the sensor types has advantages and disadvantages. Chapter 6 gives specific descrip- tions of the sensors used in this project. In that chapter, the relative merits are discussed in more detail. 1.4 Contributions of this Thesis The following contributions were made during this thesis work: • A simulation environment was developed to test the various algorithms used on the vehicle. • Hardware implementation of a lateral controller was done on a 1/10 scale model car using infrared and magnetic sensors. • Several methods of curvature estimation were developed and tested for use with the controller. • This thesis provides full documentation of the project’s hardware and software as it existed at the time of this writing. Patricia Mellodge Chapter 1. Introduction 6 1.5 Organization of this Thesis This thesis is organized as follows: • Chapter 2 describes the FLASH project for which the 1/10 scale car has been developed. • Chapter 3 gives the derivation of the car’s mathematical model and control law. • Chapter 4 provides several methods of curvature estimation for use with the controller. • Chapter 5 fully describes the simulation environment and gives simulation results. • Chapter 6 provides complete documentation of the hardware implementation of the car. • Chapter 7 gives conclusions and possibilities for future work. Chapter 2 Project Background This chapter describes the FLASH (Flexible Low-cost Automated Scaled Highway) project at the Virginia Tech Transportation Institute (VTTI). Previous work done on this project is discussed as well as the current status of the lab’s development. 2.1 Purpose 2.1.1 Scale Model Testing The FLASH laboratory was created at VTTI as one stage in the four-stage development of automated highway systems. Each of the stages is shown in Fig. 2.1 [8]. The first stage is software, during which simulations are run to ensure the viability of designs. Next, scale modeling is done and designs are tested in hardware. After scale modeling comes full scale testing, as is done on the Smart Road. Finally, the systems are deployed and made available commercially. The second stage, scale modeling, allows for the safe and inexpensive implementation of Figure 2.1: The four stages of ITS development. 7 Patricia Mellodge Chapter 2. Project Background 8 protoype designs. It is more cost effective and safer to use a scale model car rather than a full scale car for initial testing. Testing (and repairing after the inevitable crashes!) is also easier on a scale model vehicle. Additionally, a full scale protoype requires a full scale roadway on which to test, rather than the relatively small area needed for scale model testing. The FLASH laboratory fulfills this need for scale modeling. The lab itself is located in a 1600 square foot trailer at VTTI. It contains a scale roadway and several 1/10 scale cars. Each car is capable of operating manually or autonomously. The cars are described in detail in Chapter 6. 2.1.2 Eduational Exhibit Currently, an educational exhibit is being developed to educate the public about vehicle technology and ITS. The exhibit, to be displayed in the Science Museum of Virginia in Richmond and the Virginia Museum of Transportation in Roanoke, is intended to help the public understand the technology that is currently available and what will likely be available in the near future. The exhibit will include displays with which the public can interact to understand the tech- nologies being used. A concept of the exhibit layout and track is shown in Fig. 2.2. Ad- ditionally, there will be several working, fully autonomous 1/10 scale cars driving around the track. These cars will actively demonstrate the technology that is presented by the interactive displays. These technologies include: • Infrared and magnetic sensors for lateral control • Image processing for lateral and longitudinal control • Ultrasound for adaptive cruise control and obstacle detection • In-vehicle navigation and traveler information The FLASH lab also fulfills this need for developing the museum displays. In addition to the scale roadway and cars, the FLASH lab is home to the prototype interactive displays. 2.2 Previous FLASH Development Previous versions of the FLASH vehicles were capable of manual and autonomous driving in a laboratory setting. The vehicles were regular remote control (RC) cars like those available from many hobby shops. These RC cars were then modified to include the various sensors and controllers needed for autonomous driving. Complete details of this work are given in [8]. Patricia Mellodge Chapter 2. Project Background 9 Figure 2.2: Layout concept for the museum exhibit. Several modfications were made to the standard RC cars to improve their performance. The standard handheld controller was replaced by a steering console interfaced with a PC to allow for a more real-life driving position. On board the car, the steering and velocity com- mands were sent from the wireless receiver to a 68HC11 microcontoller. This microcontroller interpreted the received commands into PWM signals for the steering servo and motor. Ad- ditionally, the microcontroller implemented speed control by using feedback from an optical encoder. The 68HC11 allowed for very precise control of the velocity and steering. For autonomous driving, infrared sensors or a camera were used. The data from the infrared sensors was used by the 68HC11 to perform lateral control. Signals from the camera were sent via wireless link to a frame grabber housed in a PC. The PC then processed the image and used the information to determine steering commands. The infrared sensors and camera were not used simultaneously. The cars were powered by a single standard 7.2V NiCd RC car battery. With these batteries and all of the addtional electronics, about 15 minutes of drive time was provided. . VTTI. It contains a scale roadway and several 1/10 scale cars. Each car is capable of operating manually or autonomously. The cars are described in detail in Chapter 6. 2. 1 .2 Eduational Exhibit Currently,. Infrared and magnetic sensors for lateral control • Image processing for lateral and longitudinal control • Ultrasound for adaptive cruise control and obstacle detection • In-vehicle navigation and. exiting a highway; obstacle detection to locate other cars, pedestrians, animals, etc.; adaptive cruise control to maintain a safe speed; collision avoidance to avoid hitting obstacles in the roadway;